DESI completes largest 3D map of 47 million galaxies and quasars ahead of schedule

The Dark Energy Spectroscopic Instrument (DESI) at Kitt Peak National Observatory has finished its five-year sky survey ahead of schedule, capturing spectra from 47 million galaxies and quasars—six times more than all previous surveys combined—plus 20 million stars. This creates the most detailed high-resolution 3D map of the universe to date, exceeding initial goals of 34 million objects and offering new insights into cosmic structure and potentially weakening dark energy.

Led by the Department of Energy's Lawrence Berkeley National Laboratory, the DESI collaboration involves over 900 researchers from more than 70 institutions worldwide, including 300 PhD students. Ohio State University played a key role in instrumentation, operations, and analysis, with contributions from instrument scientist Paul Martini, lead operations scientist Klaus Honscheid, and large-scale structure catalog lead Ashley Ross. The survey faced challenges like the 2022 Contreras wildfire, which disrupted power and internet at Kitt Peak for months, but the team adapted with creative solutions for high-quality nightly data.

DESI began observations in 2021, mapping extremely faint galaxies using as few as 100-200 photons due to their distances up to 10 billion light years. It covers 14,000 square degrees of sky (with plans to expand), compared to the full sky's 41,000 degrees obscured in parts by the Milky Way. Prior maps totaled about 5 million galaxies; DESI's is nearly 10 times larger. As David Schlegel of Berkeley noted, maps grow 10-fold every decade, potentially mapping all observable galaxies by 2061.

Initial analysis of the full dataset is expected in about a year, with public release to researchers by 2027. DESI will continue through at least 2028, targeting harder-to-observe regions for refined cosmic maps and tighter constraints on parameters like dark energy, which makes up ~70% of the universe. A 2024 DESI dataset hinted it may be weakening, challenging the lambda-CDM model. Ofer Lahav of University College London highlighted the data flood: from thousands of galaxies 40 years ago to millions today, shifting challenges to analysis.

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